We're taking the pulse of the Business Intelligence and Analytics market based on our insights and our experiences with customers, colleagues, customers and partners.

Tuesday Jan 20, 2015

2014 was a busy year for Oracle Business Analytics. Here is
a look at Oracle Business Analytics top 10 moments in 2014 (in no particular
order):

10. Oracle Lays out
the Top 10 Big Data and Analytics Trends in 2014: Oracle surveyed hundreds
of IT decision makers to learn about their big data and analytics plans for
2014—both within the Oracle customer base and the industry at large. Respondents
provided specific feedback on mobile BI, cloud, Hadoop, data discovery,
predictive analytics, and decision optimization technologies and practices.
From this extensive data set we compiled the following trends: click
here.

9.Why 2015
Will Be Year of Big Data: Oracle's Seven Predictions: Neil Mendelson,
Oracle's vice president of Big Data and Advanced Analytics, is immersed in this
sector each day at his office in Redwood Shores, Calif. In a conversation with
eWEEK, he offered readers some insight into what the company is thinking—and
how big data trends will be evolving—as we all move into 2015. click
here

8. The Intelligence Guy Video Series Makes its Debut: In this series we explore important business
issues that can be addressed using Big Data and Analytics. click
here

7.Customers
Talk About the Benefits of Oracle BI Solutions at Collaborate 2014: Hear InterRel, Ameren, Hess Corp, Acadia
Healthcare, University of California Berkeley, The City of Atlanta, ADP, and
others talk about how they have achieved real business results with Oracle
Business Analytics solutions.click
here

6.Oracle BI Applications Deliver Greater
Insight Into Talent and Procurement: To empower organizations to
achieve greater visibility into their business performance and to execute with
greater agility, Oracle has announced the latest release of Oracle Business
Intelligence (BI) Applications. With new ways to seamlessly analyze procurement
data and a new module for analyzing talent, Oracle continues to extend the
opportunity for organizations to gain insight from a range of data sources and
applications. click
here

3.Oracle
Repeats as BI and Analytics Leader in Gartner MQ: For the 8th consecutive
year, Oracle is a Leader in Gartner’s Magic Quadrant for Business Intelligence
and Analytics Platform. Gartner declares that “the BI and analytics platform
market is in the middle of an accelerated transformation from Business
Intelligence (BI) systems used primarily for measurement and reporting to those
that also support analysis, prediction, forecasting and optimization.” click
here

Friday Dec 20, 2013

2013 was a busy year for Oracle Business Analytics and as it
comes to end, we wanted take a moment to thank all of our customers and
partners for another great year together. At Oracle, we enjoy a good year-end
recap so here is a look at Oracle Business Analytics top 10 moments in 2013 (in
no particular order). Relax and take a
stroll down memory lane with us!

10. The Release of Oracle
Endeca Information Discovery 3.1 – The latest release of Oracle Endeca
Information Discovery 3.1 incorporates new enterprise self-service discovery
capabilities for business users, allowing them to easily make information-based
business decisions with greater success, safety and confidence. Learn
more about Oracle Endeca

9. Big Data at Work
Webcast Series – 5 webcasts, 1000’s of attendees with featured guest
speakers from Dell, Passoker, Cloudera, Delphi, as well as MIT’s Andrew McAfee.
View
on-demand

8. Oracle Exalytics
T5-8 Scales Up to Deliver Customers with Analytic Insights– Oracle Exalytics In-Memory
MachineT5-8, the new engineered system with 4TB of memory per machine, delivers
extreme performance for business intelligence (BI) and enterprise performance
management (EPM) applications, helping organizations drive better efficiency by
speeding answers to complex business scenarios. Learn more about Oracle Exalytics

5. The Release of
Oracle BI Mobile App Designer – A
new design tool with which business users can easily create stunning and
interactive analytical applications for use on any major mobile device. With this
release, Oracle adds major innovations to Oracle Business Intelligence,
extending the capabilities of the Oracle BI Mobile solution, and reinforcing
Oracle’s commitment to empowering organizations to stay connected to their
businesses with real-time insights while on the go.
Learn more about Oracle BI Mobile App Designer

4. Oracle Exalytics X3-4 Powers Real-Time Analytical Insights – The
new system features significant software enhancements and hardware updates,
dramatically expanding the capabilities of the industry’s first high-speed
engineered system for business analytics. Learn more about Oracle Exalytics

3. The release of Oracle Business Intelligence Applications 11.1.1.7.1– Completely redesigned to increase implementation productivity, the new
release incorporates significant enhancements across the entire BI Applications
product line and introduces new in-memory analytic applications. Learn more about Oracle BI
Applications

1. Oracle Positioned in Leaders Quadrant for BI and Analytics Platforms
by Gartner – Oracle has been named Leader in Business Intelligence for the
seventh consecutive year. Read the report. Plus, Oracle customer, Land O Lakes, wins
Gartner BI and Analytics Excellence award for their innovative use of Oracle
Endeca Information Discovery. Read the story

Historic Moment - Oracle Team USA puts Big Data and Analytics to work and fuels the most dramatic victory in the history of the America's Cup. Watch
the Video

Friday May 18, 2012

It has been established beyond doubt that data and its analysis can have a huge impact on an organization’s top line and bottom line. Business Analytics helps organizations deliver better business performance in two ways – by optimizing business processes and by helping to innovate. Optimization helps organizations be efficient and effective by taking inefficiencies out of the business processes and focusing on the high impact opportunities. Innovation on the other hand helps organizations by uncovering new customer segments, new product categories, new markets, new business models etc.

The styles of analyzing data are many fold from answering questions like “what is going on?” to “why are the things the way they are?” to “what will happen if I do X or Y?” to “what does the future look like?” Broadly speaking the styles of analytics can be classified into three categories:

·Exploratory Analysis: The objective of exploratory or investigative analysis is exploration and analysis of complex and varied data – whether structured or unstructured for information discovery. This style of analysis is particularly useful when the questions aren’t well formed or the value and shape of the data isn’t well understood.

·Descriptive Analytics: The objective of this style of analysis is to answer historical or current questions like what is going on. why are the things the way they are?. This is the most common style of analysis and here the questions as well as the value and shape of data are well understood.

·Predictive Analysis: Predictive analysis aims at painting a picture of the future with some reasonable certainty.

So, what’s art of possible with business analytics? It’s the application of the above three styles of analytics to a business scenario for better insights, decisions and results. Let’s try and explain this with an example. Consider this scenario:

You are a Financial Services firm e.g. a large bank and are trying to improve profitability. You read Larry Seldon’s book titled “Angel Customers and Demon Customers” and agree with the findings that 20% of your top customers bring in 80% of the profits and would like to manage you business as a portfolio of customers as opposed to portfolio of products. So, how do you do that? The answer is business analytics.

You can start by using descriptive analytics techniques like operational reports, ad-hoc query, dashboards etc. on data collected from different sources like sales, customer service etc. to determine the profitability of each customer. You can then use predictive analysis techniques like data mining, statistical analysis to further enrich your customer data into profitability segments like high, medium, low and loss making customers. Finally, you can choose different customer service channels like personal banker, phone or ATM to cost effectively serve you customers e.g. a high profitability customer can be served by a personal banker free of charge but if the loss making customer wants a personal banker there will be a charge. Once you have implemented such programs you can use exploratory analysis to gauge the sentiment across social media channels like Facebook and Twitter to see if the programs are working as desired. Better yet you may come up with new innovative business models like mobile banking or online only banking to improve profitability.

That’s the art of possible powered by business analytics. Stay tuned, I intend to publish more examples from different industries to show the art of possible with business analytics.

Tuesday Feb 07, 2012

Enterprise systems have long been designed around capturing, managing and analyzing business transactions e.g. marketing, sales, support activities etc. However, lately with the evolution of automation and Web 2.0 technologies like blogs, status updates, tweets etc. there has been an explosive growth in the arena of machine and consumer generated data. Defined as “Big Data”, this data is characterized by attributes like volume, variety, velocity and complexity and essentially represents machine and consumer interactions.

Case for Big Data Analysis

Machine and consumer interaction data is forward looking in nature. This data available from sensors, web logs, chats, status updates, tweets etc. is a leading indicator of system and consumer behavior. Therefore this data is the best indicator of consumer’s decision process, intent, sentiments and system performance. Transactions on the other hand are lagging indicators of system or consumer behavior. By definition leading indicators are more speculative and less reliable compared to lagging indicators; however, to predict the future with any confidence a combination of both leading and lagging indicators is required. That’s where the value of big data analysis comes in, by combining system and consumer interactions and transactions, organizations can better predict the consumer decision process, intent sentiments and future system performance leading to revenue growth, lower costs, better profitability and better designed systems.

So, which business areas will benefit via big data analysis? Think of areas where decision-making under uncertainty is required. Areas like new product introduction, risk assessment, fraud detection, advertising and promotional campaigns, demand forecasting, inventory management and capital investments will particularly benefit by having a better read on the future.

Big Data Analytics Lifecycle

The big data analytics lifecycle includes steps like acquire, organize and analyze. Big data or machine/consumer interaction data is characterized by attributes like volume, velocity and variety and common sources of such data include sensors, web logs, status updates and tweets etc. The analytics process starts with data acquisition. The structure and content of big data can’t be known upfront and is subject to change in-flight so the data acquisition systems have to be designed for flexibility and variability; no predefined data structures, dynamic structures are a norm. The organization step entails moving the data in well defined structures so relationships can be established and the data across sources can be combined to get a complete picture. Finally the analysis step completes the lifecycle by providing rich business insights for revenue growth, lower costs and better profitability. Flexibility being the norm, the analysis systems should be discovery-oriented and explorative as opposed to prescriptive.

Getting Started

Oracle offers the broadest and most integrated portfolio of products to help you acquire and organize these diverse data sources and analyzes them alongside your existing data to find new insights and capitalize on hidden relationships. Learn how Oracle helps you acquire, organize, and analyze your big data by clicking here.

Thursday Nov 17, 2011

Analytics is all
about gaining insights from the data for better decision making. The business
press is abuzz with examples of leading organizations across the world using
data-driven insights for strategic, financial and operational excellence. A
recent study on “data-driven decision making” conducted by researchers at MIT
and Wharton provides empirical evidence that “firms that adopt data-driven
decision making have output and productivity that is 5-6% higher than the
competition”. The potential payoff for firms can range from higher shareholder
value to a market leadership position.

However, the vision
of delivering fast, interactive, insightful analytics has remained elusive for
most organizations. Most enterprise IT organizations continue to struggle to
deliver actionable analytics due to time-sensitive, sprawling requirements and
ever tightening budgets. The issue is further exasperated by the fact that most
enterprise analytics solutions require dealing with a number of hardware,
software, storage and networking vendors and precious resources are wasted
integrating the hardware and software components to deliver a complete
analytical solution.

Oracle Exalytics
In-Memory Machine is the world’s first engineered system specifically designed
to deliver high performance analysis, modeling and planning. Built using
industry-standard hardware, market-leading business intelligence software and
in-memory database technology, Oracle Exalytics is an optimized system that
delivers answers to all your business questions with unmatched speed,
intelligence, simplicity and manageability.

Requiring no
application redesign, Oracle Exalytics can be deployed in existing IT
environments by itself or in conjunction with Oracle Exadata and/or Oracle
Exalogic to enable extreme performance and best in class user experience. Based
on proven hardware, software and in-memory technology, Oracle Exalytics lowers
the total cost of ownership, reduces operational risk and provides
unprecedented analytical capability for workgroup, departmental and enterprise
wide deployments.